<p>This paper proposes a moving sparse spatially-separated vector-sensor array (MSSVSA) for underdetermined direction-of-arrival (DOA) and polarization parameter estimation of coherent signals. The proposed array utilizes the motion to achieve a synthetic array including original and shifted arrays with extended aperture, and simultaneously reduces both inter-element coupling and inter-polarization coupling by enlarging the spacings between antennas. A decorrelation technique based on movement of the synthetic array is introduced, enabling the use of subspace-based algorithms for parameter estimation. Simulation results illustrate that the MSSVSA can achieve superior performance in parameter estimation for coherent signals under underdetermined cases, outperforming the existing techniques in terms of high-accuracy.</p>

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Underdetermined DOA and Polarization Parameter Estimation for Coherent Signals Exploiting Moving Sparse Vector-Sensor Array

  • Guojun Jiang,
  • Shaobo Wang,
  • Jiacheng Huang,
  • Yunlong Yang

摘要

This paper proposes a moving sparse spatially-separated vector-sensor array (MSSVSA) for underdetermined direction-of-arrival (DOA) and polarization parameter estimation of coherent signals. The proposed array utilizes the motion to achieve a synthetic array including original and shifted arrays with extended aperture, and simultaneously reduces both inter-element coupling and inter-polarization coupling by enlarging the spacings between antennas. A decorrelation technique based on movement of the synthetic array is introduced, enabling the use of subspace-based algorithms for parameter estimation. Simulation results illustrate that the MSSVSA can achieve superior performance in parameter estimation for coherent signals under underdetermined cases, outperforming the existing techniques in terms of high-accuracy.